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Transformer fault diagnose intelligent system based on DGA methods.

Saad A Mohamed Abdelwahab1, Ibrahim B M Taha2, Rizk Fahim3

  • 1Electrical Department, Faculty of Technology and Education, Suez University, P.O.BOX: 43221, Suez, Egypt. Saad.Abdelwahab@suezuniv.edu.eg.

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Summary

This study introduces a Transformer Fault Diagnosis Intelligent System (TFDIS) to improve power transformer fault detection. The TFDIS integrates multiple Dissolved Gas Analysis (DGA) methods, achieving higher diagnostic accuracy than individual techniques.

Keywords:
And intelligent systemArtificial intelligenceDGAPower transformers

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Area of Science:

  • Electrical Engineering
  • Power Systems
  • Artificial Intelligence

Background:

  • Power transformers are critical infrastructure; malfunctions cause significant economic losses for utilities.
  • Transformer failures stem from electrical, thermal, and mechanical stresses on insulation (oil and paper).
  • Dissolved Gas Analysis (DGA) is standard for fault detection, but traditional methods (IEC Code, Rogers Ratio, Duval triangle) have limited accuracy.

Purpose of the Study:

  • To develop an advanced intelligent system for enhanced power transformer fault diagnosis.
  • To improve the diagnostic accuracy of existing Dissolved Gas Analysis (DGA) methods.
  • To create a Transformer Fault Diagnosis Intelligent System (TFDIS) by integrating multiple DGA techniques.

Main Methods:

  • Developed a Transformer Fault Diagnosis Intelligent System (TFDIS).
  • Integrated outputs from four DGA methods: Code Tree 2020, modified IEC, Rogers' Ratio, and Neural Pattern Recognition.
  • Compared the diagnostic accuracy of the integrated system against individual methods.

Main Results:

  • The developed TFDIS achieved a diagnostic accuracy of 89.12%.
  • This accuracy surpasses the highest individual accuracy of 86.01% obtained by Neural Pattern Recognition.
  • The integrated approach significantly enhances analytical accuracy in diagnosing transformer faults.

Conclusions:

  • The Transformer Fault Diagnosis Intelligent System (TFDIS) offers superior fault diagnostic accuracy compared to individual DGA methods.
  • Integrating multiple DGA techniques within an intelligent system framework is effective for reliable power transformer health monitoring.
  • The TFDIS represents a significant advancement in ensuring power system reliability and reducing utility losses.